Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Jun 2017
Research article |
| 02 Jun 2017
Atmospheric turbulence affects wind turbine nacelle transfer functions
Clara M. St. Martin
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences (ATOC), University of
Colorado at Boulder, 311 UCB, Boulder, CO 80309, USA
Julie K. Lundquist
Department of Atmospheric and Oceanic Sciences (ATOC), University of
Colorado at Boulder, 311 UCB, Boulder, CO 80309, USA
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
Andrew Clifton
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
Gregory S. Poulos
V-Bar, LLC, 1301 Arapahoe Street, Suite 105, Golden, CO 80401, USA
Scott J. Schreck
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
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- Development of a novel method for the correction of the nacelle wind speed in stall-controlled wind turbines L. Vivas et al. 10.1088/1742-6596/2767/3/032008
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham 10.1007/s10409-020-00934-7
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- The 15-year operational experiences of an 850 kW peri-urban wind turbine: Lessons learned from a behind-the-meter installation in Ireland R. Byrne & P. MacArtain 10.1016/j.esd.2022.08.011
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. 10.1088/1742-6596/1618/5/052007
- Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements H. Asmuth et al. 10.2139/ssrn.3940154
- Wind Turbine Power Curve Monitoring Based on Environmental and Operational Data S. Cascianelli et al. 10.1109/TII.2021.3128205
- Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project J. Zhang et al. 10.3390/en16052193
- Diagnosis of wind turbine systematic yaw error through nacelle anemometer measurement analysis D. Astolfi et al. 10.1016/j.segan.2023.101071
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. 10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt 10.5194/wes-4-343-2019
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques D. Astolfi et al. 10.1016/j.segan.2024.101417
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. 10.3390/en14041105
- Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements H. Asmuth et al. 10.1016/j.renene.2022.04.047
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- Observing and Simulating Wind-Turbine Wakes During the Evening Transition J. Lee & J. Lundquist 10.1007/s10546-017-0257-y
- Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis D. Astolfi et al. 10.3390/en14040915
20 citations as recorded by crossref.
- Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind Z. Wu et al. 10.1002/we.2477
- Wind Turbine Multivariate Power Modeling Techniques for Control and Monitoring Purposes D. Astolfi et al. 10.1115/1.4048490
- Development of a novel method for the correction of the nacelle wind speed in stall-controlled wind turbines L. Vivas et al. 10.1088/1742-6596/2767/3/032008
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham 10.1007/s10409-020-00934-7
- Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement H. Kim & J. Kim 10.3390/en14082319
- The 15-year operational experiences of an 850 kW peri-urban wind turbine: Lessons learned from a behind-the-meter installation in Ireland R. Byrne & P. MacArtain 10.1016/j.esd.2022.08.011
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. 10.1088/1742-6596/1618/5/052007
- Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements H. Asmuth et al. 10.2139/ssrn.3940154
- Wind Turbine Power Curve Monitoring Based on Environmental and Operational Data S. Cascianelli et al. 10.1109/TII.2021.3128205
- Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project J. Zhang et al. 10.3390/en16052193
- Diagnosis of wind turbine systematic yaw error through nacelle anemometer measurement analysis D. Astolfi et al. 10.1016/j.segan.2023.101071
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. 10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt 10.5194/wes-4-343-2019
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi 10.3390/machines9050100
- Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques D. Astolfi et al. 10.1016/j.segan.2024.101417
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. 10.3390/en14041105
- Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements H. Asmuth et al. 10.1016/j.renene.2022.04.047
- False alarm detection in wind turbine by classification models A. Peco Chacón et al. 10.1016/j.advengsoft.2023.103409
- Wind Turbine Operation Curves Modelling Techniques D. Astolfi 10.3390/electronics10030269
- Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression D. Astolfi & R. Pandit 10.3390/app12010072
2 citations as recorded by crossref.
Latest update: 15 Nov 2024
Short summary
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence of atmospheric stability and turbulence regimes on nacelle transfer functions (NTFs) used to correct nacelle-mounted anemometer measurements. This work shows that correcting nacelle winds using NTFs results in similar energy production estimates to those obtained using upwind tower-based wind speeds. Further, stability and turbulence metrics have been found to have an effect on NTFs below rated speed.
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence...
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